東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Fuzzy logic optimization of injectio...

Sillo, Firmin Z.

Linked to FindBook

Google Book

Amazon

博客來

Fuzzy logic optimization of injection molding of liquid silicone rubber.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fuzzy logic optimization of injection molding of liquid silicone rubber./
Author:	Sillo, Firmin Z.
Description:	95 p.
Notes:	Source: Masters Abstracts International, Volume: 43-05, page: 1805.
Contained By:	Masters Abstracts International43-05.
Subject:	Plastics Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1425525
ISBN:	0496987542

Fuzzy logic optimization of injection molding of liquid silicone rubber.
Sillo, Firmin Z.

Fuzzy logic optimization of injection molding of liquid silicone rubber. - 95 p.

Source: Masters Abstracts International, Volume: 43-05, page: 1805.

Thesis (M.S.Eng.)--University of Massachusetts Lowell, 2005.

Liquid Silicone Rubber (LSR) is rapidly growing and emerging among the materials used for injection molding. In recent years, there has been an increasing demand for high quality LSR products.

ISBN: 0496987542Subjects--Topical Terms:

1023683
Plastics Technology.

Fuzzy logic optimization of injection molding of liquid silicone rubber.
LDR:02367nmm 2200325 4500 001 1814022
005 20060503082231.5
008 130610s2005 eng d
020 $a 0496987542
035 $a (UnM)AAI1425525
035 $a AAI1425525
040 $a UnM $c UnM
100 1 $a Sillo, Firmin Z. $3 1903503
245 1 0 $a Fuzzy logic optimization of injection molding of liquid silicone rubber.
300 $a 95 p.
500 $a Source: Masters Abstracts International, Volume: 43-05, page: 1805.
500 $a Supervisor: Francis Fang Lai.
502 $a Thesis (M.S.Eng.)--University of Massachusetts Lowell, 2005.
520 $a Liquid Silicone Rubber (LSR) is rapidly growing and emerging among the materials used for injection molding. In recent years, there has been an increasing demand for high quality LSR products.
520 $a This research highlights LSR chemistry, its processing technology and tooling design since these areas are necessary to master the performance of an injection molding. It then presents an overview of the fuzzy logic language and provides a fuzzy inference system to improve the process.
520 $a Using a Design of Experiment based on the Taguchi method, the research was able to indicate the three most critical parameters of the LSR injection molding process: mold temperature, injection speed and cure time. These parameters were used as the inputs of the fuzzy inference system. The molded part weight, dimension, and visual characteristics were used as the outputs. The statistical process capability studies between the experimental runs with and without the fuzzy inference system indicated that the fuzzy logic system was found to be effective in optimizing the process. It was also found that during the course of the study the correlation between pressure, volume and temperature (P-V-T) could be very helpful in developing a more effective fuzzy inference system. This system would include additional parameters as inputs. It would also provide a closed loop control system for a self-regulating LSR injection molding.
590 $a School code: 0111.
650 4 $a Plastics Technology. $3 1023683
650 4 $a Engineering, Materials Science. $3 1017759
650 4 $a Engineering, Industrial. $3 626639
650 4 $a Artificial Intelligence. $3 769149
690 $a 0795
690 $a 0794
690 $a 0546
690 $a 0800
710 2 0 $a University of Massachusetts Lowell. $3 1017839
773 0 $t Masters Abstracts International $g 43-05.
790 1 0 $a Lai, Francis Fang, $e advisor
790 $a 0111
791 $a M.S.Eng.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1425525